The importance of data in modern technology is not to be underestimated; because there are so many services and products, there are many reasons and channels for collecting users or corporate data. The company uses data to improve customer experience, and inside requires effective data accumulation to maintain recording and efficient operation. When we call and advocate a smoother experience in our business and daily operations, we are creating a channel to collect and use more data from the movement process.
In fact, we say that the company and organization should “refresh” all the reasons to make our service or operations faster. However, the improvement of this speed or service quality can only be implemented when the operation is automated, that is, the digital record of this operation, and then when it wants to repeat, the human resources it happens less because of the available data It is enough to automate operations.
Sometimes you may not need the previous event to dynamize it, we only need to program any digital platform or channel we use to seamlessly perform operations, no need to manually or with minimal people. The problem is that as more and more companies go to digitization, more and more transactions or services become automated, collect and store more data to improve efficiency.
The problem is that not only B2C needs to collect these data to meet their customers’ needs, B2B companies need. “SaaS or ERP” also must collect data from the size of their services. In fact, the company will collect a lot of data every day, because they not only collect customer data, but also collect internal operations, not only smooth and simple operations. As this emergence, some companies have developed a business model to help other companies store data in “Cloud”.
Cloud computing services help these other companies (regardless of size) reduce worry about users and business data. These cloud services provide companies including e-commerce giants, Amazon Network Services (Amazon, Google’s Google Cloud service, and even Microsoft’s Microsoft Azure.
In order to improve user experience and stay competition (obviously, each level of technology also has its own competition), these cloud service providers have begun to use tentacles and massive data to create “smart services” and products for their customers. . They use machine learning to provide many smart services for their customers and customers, such as Amazon’s Alexa and Google’s Google Voice Assistant and other well-known virtual assistants. The essence of machine learning is to efficiently use the cloud-available massive data available, so that the products are smarter, and the service is more efficient.
On the other hand, the block chain technique seems to be a completely different animal. Although this technology also involves data management, the block chain is more about privacy, transparency, and data security. It uses password and dispersion data management to effectively protect user data and rapidly become one of the most important modern technologies.
However, these three forms of data management techniques do not seem to make progress as we expect, especially as a coordinated unit. If these three forms of technology – cloud computing, machine learning and block chain technology – can result in effective use, will result in huge benefits. In fact, I predict future technical data management will involve the strategic application of these three technologies. In this article, we will analyze each technique and its characteristics, and we will also understand where they are and how to intersect, and most importantly, their commitment to the IT industry.
According to Microsoft Azure, cloud computing is to provide computing services – servers, storage, database, network, software, analysis, and the Internet (“cloud”). Companies that provide these computing services are called cloud computing providers, which typically charge cloud computing services based on the usage, similar to how your water and electricity is paid at home.
Cloud computing has become an important aspect of modern technology. The demand for data storage results in personal and legal entities to be forced to find ways to store data. For individuals, hardware seems to be the most realistic way to achieve this goal because people use flash drives or USB hard drives to store their data and files.
On the other hand, the company has more data reserved responsibility, because they not only store customer data, but also store data on their internal operations. These companies use physical data centers (buildings occupied by the server), the greater the company, the more data centers needed to store all the data required by the company.
In fact, the purchase and upgrade of the hard drive to increase the size of the organizational data server is the lowest aspects of the data center requirements. With the company’s expansion and attracting more customers, they must ensure that they continue to extend their storage capacity to serve more and more users on their platform. This may be very difficult, sometimes we will hear cases that cause the server or software crash due to the shortage of users in the user’s capacity. The fact is that the cost and workload of the personal or organization use data storage hardware is very high, and in most cases, it is necessary to more user-friendly software or a better digital alternative.
DrOPBOX and Google Drive have been actively trying to solve individual data storage problems, but most of the true essence of cloud computing is B2B. In terms of providing services for business organizations, cloud computing is more advantageous as a department in the technical industry, and more influential. As mentioned earlier, these companies must store and store large amounts of data that cause a better development of better solutions. Not surprisingly, the main participants in the cloud computing field is a large-scale technology company that has been famous in the information technology field. The three most important cloud computing services are Amazon AWS (Amazon Network Services), Google Cloud Service, Microsoft Azure. AWS is in a leading position in the market share and is still the most profitable channel of this e-commerce giant, which proves the profitability of cloud computing services. However, just like the definitions of cloud computing already given above, these services are similar to the regular subscription mode and charge customers based on the use. The fee may focus on the function of the organization, the subscription plan’s duration or the number they will provide services.
Artificial intelligent machine algorithm
The entire meaning of technology is automation. More zone chain messages, please pay attention to the download area block APP, the Global Block Chain Regulatory query app. There are almost no computers or machines that can do things. However, in order to save time and effort, we built machines and computers to help us do these things. The main value of these machines and computers is that they can repeat that we have an outsourcing process or action. This repetition-almost no trouble – is called automation.
It is almost impossible to talk about innovation without pointing out their ultimate goal is automation. Therefore, with the continuous development of modern technology, more data is needed in the technical field, we must start to find a way to improve the level of automation of data management and “independent thinking”.
Automation or independent thinking in this data management process is called machine learning. Machine learning can be simply described as how the machine is “learning” by looking for models in similar data. The machine here may mean the existing algorithm, and the learning process now involves providing more data or information to the algorithm, making it interacts with it, screens, connect points, all of which are to find more in the entire data structure. Mode, or to become smarter.
A more intelligent concept indicates that the machine (algorithm) is given more information – mainly related to existing information – it is now associated with existing information in order to better understand its most important responsibilities, Or first prepare it. The entire concept of machine learning is that more and more data is received as programs, it starts to understand more and solve more problems. Machine learning is similar to automation, but more like data automation.
Most people don’t even know that we have interacting with machine learning almost every day. Google Algorithm and other software platforms can make predictions or make our query adapt to previously matched searches, which are examples of machine learning. These algorithms have become accustomed to your internet research, and over time becomes more intelligent, they can predict that you are most likely to take the next step.
There are several ways to train the machine (algorithm). All this depends on how to drive a car. Learning can be supervised, partially supervised or not supervised.
Block chain: distributed account
If you have created a document and share with Google documents, you agree that the document seems to be distributed, but not necessarily shared. Everyone can access documents simultaneously, and every change in the document is usually recorded in real time, and these changes are transparent to everyone, because no one is forced to block every time you do this.
Although block chain technology is more complex than Google Docs, the above illustrations can be well explained well of the working principle of the block chain technology.
The block chain is basically a digital record of the transaction, replication and distribution in a computer system network in the chain. The block chain is collected in the form of a group, also known as a block, which has a certain storage capacity, and is attached to the previous fill block, thereby forming a chain or data chain, called “block chain”. All new information after the newly added block is compiled into a newly formed block, and then it will also be added to the chain after filling. The purpose of the block chain is to allow logging and distributing digital information, but cannot be edited. Each block in the chain contains many transactions, and each time a new transaction occurs on the block chain, the transaction records are added to each participant’s classification account.
The block chain guarantees security and transparency. The technology acts as a dispersion system for recording and recording transactions that use a specific digital currency. Block chain technology allows transactions that use specific digital currencies (such as bitcoin) to transparently, most importantly, without banks such as banks.
Block chain technology is one of the foundations of modernization of modernization and is the proprietary technology behind the first major digital currency (bitcoin). With the area block chain technology, the encrypted currency like Bitcoin can operate in a decentralized manner. Block Chain Techniques allow encryption transactions in all classified accounts, thereby eliminating these transactions without a single central organization. One of the key features of the block chain is the invariance; the block chain technology ensures that anyone cannot change any data on the network without the consent of all network participants. Block chain technology has added trust, as the central organization (such as bank) can determine how people in the block chain can absolutely control their funds without allocating your funds without your license or consent.
Why do these three will define the future of modern technology?
Speaking of cloud computing, machine learning and block chain technology will define the future of modern technology seems to be a bit exaggerated.
It is difficult to say that it has been revealed in the detailed explanation of these three technologies that have played in the IT field. It is difficult to say that they play an important role in the industry. Today, cloud computing seems to be a “normal” service for companies and individuals, and there will be so many SaaS platforms every day. Machine learning seems to be the main driving force of competition, as the company tries to improve user experience, and the block chain technology is increasingly using a broader use case, especially from the field of encryption.
In addition to utility and noise, how will these three technologies play an important role in future technology industries? This is the topic of this article, which is also the cause of any argument or forecast. It should be noted that the fusion of these three has occurred, especially the combination of machine learning and block chain technology, but why they play an important role in future technology?
The detailed understanding of the three technical forms described herein has laid the foundation and helps readers understand their indispensable role in society and the entire technology industry. Obviously, although they seem to be useful from the perspective of data management, they seem to have specific and defined roles.
However, as discussed in this paper, the importance of data in our era is not underestimated. It is this importance that makes the three technologies in the current and future integration more likely and more inclusive.
The reality is that as more and more people go to digital, virtualization, or remote, more and more companies will need to store more data. On the other hand, with the more intelligent, smarter, more efficient products, better use of these data, will increase. In addition, with more data every day, it now comes down to the existing data trust and privacy issues.
Therefore, it is difficult to bet cloud computing, the popularity of machine learning and block chain technology will be larger, but it is more difficult to bet these three “alliances”.
First, cloud computing is intended to make companies and individuals to store data more affordable, but machine learning makes these organizations to solve problems in smarter and create smarters for global customers and users. The zone chain is set to the system to increase more security layers, which invariates the dynamics of many departments and industries.
The cloud service supported by the block chain ensures that the data stored in the cloud will not be changed or tampered with. This opportunity can truly change the industry or even the entire manufacturing process. Unlike traditional manufacturing processes, in the block chain, records are stored and distributed to nodes in the network, which is considered to be an efficient, secure, and transparent way to record transactions and important data, making records difficult to change or forgery. This ensures the safety of transparency and industrial and manufacturing processes. But not only, this is the wonderful place to combine these technologies; through machine learning, maintenance plan and preventive maintenance can be implemented throughout the process, saving to the budget from the record, which has passed cloud support The chain is so safe and transparent. All of this reduces production and production time, and makes the process more smoothly and efficient.
The same class is suitable for almost all technology to maximize their performance. E-commerce and retail platforms can also maximize their supply chain because block chain technology allows inventory management or storage data transparent and efficient. Since clouds are already primary data storage, these companies can improve their operations by making them more transparent and combining them with existing machine learning technologies used by these companies. In 2018, IBM and Twiga Foods launched a small credit based on the block chain in 2018. They also use machine learning to improve the entire process, using machine learning to create an efficient credit score system.
However, the extra wonderfulness of these trows is that they are perfectly integrated and why their smooth match is so promising. People can only imagine the combined use cases, that is, cloud computing should first appear in data storage, then the block chain is in terms of data transparency or invariance, and finally the machine learning is intelligent or idea in data maximization.
However, this is not the only dynamic that may appear in this combination. For example, another use case is trained to explore the smart model of big data available to the company and how to quickly extract from a large amount of data and transfer it to the block chain to ensure that it is not changeable.
This is very important, because in the next few years, as the company tries to maintain a competitive advantage, the driving force for collecting more data will only increase. However, these voices and pursuit of more data have also caused some companies to collect unnecessary or inaccurate data from time to time. Therefore, with the help of machine learning, these companies can intelligently use the correct data, send them to the block chain to ensure that it is not variable. In this case, the block chain represents data mining and processing activities that are more intelligent than ever. In addition, the combination of block chains and machine learning can also help reduce fraud and insecurity, especially in financial services. Although block chain technology is one of the safest technologies, but uses a simple private key or public key to complete the transaction also make it a common place for fraud. Therefore, financial services can be more secure by combining machine learning with some block chain verification and registration processes, because machine learning can help detect and track abnormal or suspicious attempts.
A typical example of how the machine learning how to track fraud is that PayPal has created an algorithm that combats identity or robot signature early. Captcha and other forms of machine learning algorithms are created in the past.
In the end, it is obvious that data will become more important in today’s technology, and people will try innovative and look for methods to ensure proper management, use and protection of data collected or excavated. The emergence of cloud computing services, machine learning and block chain technology pushes data management to new heights, but in order to meet the growing demand for trust, security, privacy, and enhancement, these three forms of technology is likely Will play a role together. Play an important role in achieving these goals in the technical industry.